LLM AIOps Development Engineer - Data Center Networking

TikTok Inc.; Seattle (WA); On-site; USD 150,000 - 190,000; Full time

Job summary

TikTok Inc. in Seattle is seeking a passionate development engineer to join the Network Observability Team.

You will help build autonomous, data-driven network operations by integrating telemetry from gNMI, Netconf, IPFIX/NetFlow, and SNMP to power AI-enabled diagnostics. You will apply ML/DL techniques to detect anomalies and pinpoint root causes across the stack, from hardware to application traffic, and explore innovative applications of large language models to improve network reliability

Responsibilities

• Build a Panoramic Network Observability Platform: streaming telemetry from gNMI, Netconf, IPFIX/NetFlow, SNMP for real-time AI-enabled data.
• Develop Intelligent Diagnostics: ML/DL for anomaly detection, correlation, noise reduction across metrics, logs and events.
• Explore Innovative Applications of LLMs and

Job description

Responsibilities

About the team

Networking brings together innovative ideas and technologies from network architecture, software defined networking (SDN), network virtualization, switch software and hardware co-design, and high-speed networking, to create hyper-scale data-center networking solutions that power several of the most popular apps of the world such as Douyin and TikTok which serve hundreds of millions of users around the globe.

Network Observation team is committed to building a world-leading hyperscale data center network infrastructure that supports hundreds of millions of users' real-time access and explosive growth of massive data volumes. We believe that the next generation of network operations will be fundamentally powered by artificial intelligence technologies, particularly Large Language Models (LLMs).

We are seeking a passionate development engineer who combines deep networking expertise with innovative AIOps capabilities to join us in defining and building "autonomous" data center networks. Together, we will transform network operations from a reactive "firefighting" mode into a proactive, data-driven intelligent ecosystem with predictive and self-healing capabilities.

Responsibilities:

• Build a Panoramic Network Observability Platform: Develop a streaming telemetry data pipeline for both physical and virtual networks, integrating multi-source data from gNMI, Netconf, IPFIX/NetFlow, and SNMP to provide a high-quality, real-time data foundation for AIOps.
• Develop an Intelligent Diagnostics and Root Cause Analysis System: Apply machine learning and deep learning algorithms to perform anomaly detection, correlation analysis, and intelligent noise reduction on massive volumes of network metrics, logs, and events. Swiftly pinpoint root causes of failures across the entire stack, from optical transceivers and switch hardware to protocol adjacencies and application traffic.
• Explore Innovative Applications of LLMs and